Molecular Me http://isbmolecularme.com Our Science. Your Wellness. Fri, 06 Dec 2013 20:33:14 +0000 en-US hourly 1 http://wordpress.org/?v=3.7.1 Lee Hood at World Stem Cell Summit http://isbmolecularme.com/lee-hood-at-world-stem-cell-summit/ http://isbmolecularme.com/lee-hood-at-world-stem-cell-summit/#comments Fri, 06 Dec 2013 20:33:14 +0000 http://isbmolecularme.com/?p=2070 Genetic Engineering & Biotechnology News offered some highlights from the World Stem Cell Summit, where ISB president, Dr. Lee Hood, gave today's keynote talk:

“In 5 to 10 years, you will have your genomes as part of your medical records,” Leroy Hood, M.D., Ph.D., Institute for Systems Biology, told attendees of the World Stem Cell Summit 2013 today, in San Diego. “Third-generation sequencing will be revolutionary,” he said in his plenary keynote “Systems Approaches to Disease and Stem Cells”; using nanopore technology it will enable sequencing of a human genome in about 15 minutes at a cost of less than $100. – GenEng News

Read the full story.

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ISB Researchers Develop New Method to Study and Predict Traits of Cells http://isbmolecularme.com/isb-researchers-develop-new-method-to-study-and-predict-traits-of-cells/ http://isbmolecularme.com/isb-researchers-develop-new-method-to-study-and-predict-traits-of-cells/#comments Thu, 05 Dec 2013 22:26:23 +0000 http://isbmolecularme.com/?p=2058 3 Bullets:
  • ISB researchers used the systems approach to develop a new way to integrate data from different classes of networks to better understand how cells function.
  • The method is a software program called GEMINI and it’s the first of its kind to integrate data from metabolic networks to refine transcriptional regulatory networks.
  • GEMINI has higher success rate than existing technologies.

By Matt Richards

In a study published on Dec. 5, 2013, in the journal PLOS Computational Biology, researchers at Institute for Systems Biology describe the first use of a genome-scale metabolic network of yeast to refine a gene regulatory network. This method, called GEMINI (Gene Expression and Metabolism Integrated for Network Inference), is a software program that permits the integration of data from different classes of networks in order to better understand how cells function and what traits they express.

Every cell in your body contains identical copies of your DNA. But how those cells differentiate into, say skin cells or lung cells, is the result of interactions that take place in the transcriptional regulatory network (TRN). The TRN is essentially a map of how all the genes in an organism interact to mediate all the body’s functions. Researchers long have tried to model TRNs in order to better understand the underlying molecular processes that cause cells to change. With this understanding, researchers can better predict how cells will respond to perturbations such as disease.

The current practice of reconstructing TRNs generally uses data only from the respective network. While it’s possible to construct TRNs this way, it creates too many potential molecular interactions to identify efficiently what interactions actually exist in the cell. But because the actions of one network affects the actions of another network, researchers in the Price Lab at ISB hypothesized that by using the well-established information from genome-scale metabolic networks of yeast – a model organism – they could refine the information from TRNs and achieve better agreement with biological mechanisms.

Having a systems understanding of how these cellular networks function together can lead the way to a wide range of applications in biotechnology, drug discovery and diagnostics. Learn more about GEMINI.

About Matt Richards: Matt Richards is a graduate student in the Price Lab. He is member of the ISB Editorial Board.

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The Future of Healthcare is Personalized http://isbmolecularme.com/the-future-of-healthcare-is-personalized/ http://isbmolecularme.com/the-future-of-healthcare-is-personalized/#comments Wed, 04 Dec 2013 07:31:26 +0000 http://isbmolecularme.com/?p=2051 Dr. Lee Hood, founder and president of Institute for Systems Biology, appeared on the news in New Zealand after giving a talk the previous night at the University of Auckland. Click on the image below to watch the video.

Lee Hood in NZ

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ISBers Doing Cool Things: Running a Marathon on Antarctica http://isbmolecularme.com/isbers-doing-cool-things-running-a-marathon-on-antarctica/ http://isbmolecularme.com/isbers-doing-cool-things-running-a-marathon-on-antarctica/#comments Mon, 02 Dec 2013 23:00:36 +0000 http://isbmolecularme.com/?p=2046 Allison Lee, a research associate at ISB who blogged about her research cruise on the Ross Sea in Antarctica, recently wrote a piece for Northwest Runner about her experience running a marathon at McMurdo Station. In a banana costume. You can read her account (Antarctica Marathon Article). You can read about her research in Antarctica and view some of the wonderful photos of ice, algae and penguins here.

Northwest Runner

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ISB’s PeptideAtlas Helps Advance the Study of Proteins http://isbmolecularme.com/after-the-genome-the-proteome/ http://isbmolecularme.com/after-the-genome-the-proteome/#comments Fri, 22 Nov 2013 21:32:39 +0000 http://isbmolecularme.com/?p=1967  

3 Bullets

  • The Human Proteome Project expands on the work of the Human Genome Project.
  • ISB is a leader in proteomics and developed PeptideAtlas, a project that has cataloged the proteins observed in thousands of proteomics experiments as an open resource for researchers everywhere.
  • In a new report, ISB researchers show that PeptideAtlas now contains proteins from about 62 percent of human genes thought to encode proteins.

By Terry Farrah
Software Engineer, Moritz Group

The Human Genome Project (HGP), declared complete ten years ago, was a defining and important step toward understanding how the human organism works. However, a lot of work remains to make full use of the genome in the practice of medicine. The Human Proteome Project (HPP,  www.thehpp.org) is one of several international projects expanding on the HGP.

Proteins are complex molecules that perform a universe of biological processes, and the genome is essentially a set of instructions for making proteins. Some genes appear to encode proteins but those proteins seem to never get made, similar to an architectural plan for a building that is never built. Figuring out which genes actually produce proteins is an initial goal of the HPP, and the PeptideAtlas project at ISB is a key tool in assessing progress toward that goal.

In a paper published online today in the Journal of Proteome Research by Terry Farrah, Eric Deutsch, and co-workers in the Moritz group, as well as prominent collaborators, PeptideAtlas is used to show that there is reliable mass spectrometry-based proteomics evidence for the protein products of 12,644 genes, or 62 percent of all the genes thought to encode proteins. This is an increase of 5 percent over last year. Because proteomics laboratories are now using our list as a guide to target the remaining proteins, this rate of increase is likely to accelerate.

The word proteome refers to the complete set of proteins made by an organism, and proteomics is a set of technologies, primarily using mass spectrometry, for determining which protein molecules exist in a biological sample—a vial of blood, for instance. PeptideAtlas collects the results of hundreds of human proteomics experiments performed around the world and processes them together to produce a single protein list with a very low error rate. If you just combine the protein lists reported for each experiment, you end up with a very high error rate that makes the combined list almost useless. It is PeptideAtlas’s low error rate that allows us to accurately estimate how far the global proteomics community is toward completion of the HPP's initial goal. This report provides the community the current status of the world’s effort in defining the Human proteome and the list of putative missing proteins remaining to be identified.  

Also in today’s publication, we separate our human proteomics data according to its source to create protein lists specific to kidney, urine, and blood plasma. The kidney filters plasma and releases waste into the urine, so these three tissue/biofluid-based proteomes are intimately related. By cataloging the proteins found in each, we assist researchers who are developing biomarker panels for predicting, diagnosing, and monitoring diseases of the kidneys and urogenital tract, similar to the ground-breaking biomarker panel recently announced by our collaborators at Integrated Diagnostics for characterizing pulmonary nodules. Thus, ISB’s PeptideAtlas contributes toward both our basic understanding of biology and the advancement of personalized medicine.

About Terry Farrah: Terry is a software engineer in the Moritz Group at ISB. She is an at-large member of ISB's Editorial Board.

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Valerie Logan Luncheon Raises $50K for Science Education Programs at ISB http://isbmolecularme.com/valerie-logan-luncheon-raises-50k/ http://isbmolecularme.com/valerie-logan-luncheon-raises-50k/#comments Fri, 22 Nov 2013 18:21:07 +0000 http://isbmolecularme.com/?p=1970 The Second Annual Valerie Logan Luncheon, which took place on Nov. 13, raised just over $50,000 for our education programs at Institute for Systems Biology.

Guest speaker Julia Joo, who spent her summer as a high school intern here at ISB, shared with us the educational journey that led her to choose science as a career path. “Where my science classes and exposure to local scientists planted the seed of a deep interest in scientific discovery, ISB is truly where the flower of my passion for research bloomed to fruition,” Joo said.

ISB's president, Dr. Lee Hood, presented the Valerie Logan Leadership in Science Education Award to Dr. Meena Selvakumar, the acting vice president of Strategic Programs at the Pacific Science Center. Among her many achievements, she developed and directs the Portal to the Public Initiative, which focuses on creating opportunities to expose a general audience of all ages to current scientific research and also to train scientists in how to better communicate their work to a lay audience.

"This has been a true highlight for me," Dr. Selvakumar said.

Dr. Hood also announced that ISB is creating a strategic plan that enumerates new possibilities for how systems biology can continue to catalyze fundamental changes not only at levels K-12 but also at the undergrad and even graduate levels. "In keeping with all our past successes and this emerging vision – and to honor Valerie Logan – we're going to rename our program as the Logan Center for Education," Dr. Hood said.

The education team will share more detailed information about the Logan Center and the education strategic plan in early 2014.

Thank you to all of ISB's supporters and partners (including corporate sponsors Boeing, Touchstone, Iverson Genetics, KeyBank and Salal Credit Union) who make it possible for us to continue Valerie’s vision to inspire an ever-growing number of students like Julia to seize opportunities and excel, and to honor leaders in science education.

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ISB on Cover of C&En Magazine http://isbmolecularme.com/isb-on-cover-of-cen-magazine/ http://isbmolecularme.com/isb-on-cover-of-cen-magazine/#comments Tue, 19 Nov 2013 19:03:31 +0000 http://isbmolecularme.com/?p=1972 By ISBUSA

ISB researcher Sarah Li was featured on the cover of C&EN Magazine on Nov. 18. The cover story is about how instrumentation companies are teaming up with research organizations to gain access to valuable work that could help refine or develop new technologies. ISB's Dr. Robert Moritz comments about our collaboration with AB Sciex for the story.

Excerpt from the piece:

"Building on this work, AB Sciex formed a partnership with the Institute for Systems Biology, a Seattle-based nonprofit headed by Leroy Hood. In February, ISB and AB Sciex signed a three-year agreement to collaborate on developing MS methods and technology in proteomics, applying SWATH to build biomarker libraries.

ISB scientists have known people at AB Sciex for many years, says Robert L. Moritz, ISB’s research director for proteomics. “We have had very much aligned thoughts about advancing proteomics. The latest partnership was more formalized because it was much larger.” ISB uses AB Sciex instruments, and the two sides exchange people and expertise."

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A ‘Sound Check’ for Digital Transcriptomes http://isbmolecularme.com/a-sound-check-for-digital-transcriptomes/ http://isbmolecularme.com/a-sound-check-for-digital-transcriptomes/#comments Wed, 06 Nov 2013 22:18:19 +0000 http://isbmolecularme.com/?p=1915 3 Bullets:
  • Looking for biomarkers in different types of tissues requires comparing massive amounts of gene expression data.
  • In order to compare 'digital transcriptome' data, they have to be normalized or adjusted to a common standard of measurement.
  • ISB researchers developed new algorithmic methods that outperform existing methods for normalizing gene expression data from different samples.

By Dr. Martin Shelton

Identifying genes that are expressed at one level in disease and at another level in healthy tissue — so called differentially expressed genes — is one of the first steps in biomarker identification. RNA-seq, which is the application of next-generation sequencing to study transcribed RNA sequences, allows researchers to measure the expression levels of thousands of genes from multiple samples.

However, before comparing gene expression data from different samples to identify differentially expressed genes, the data must be re-scaled, or normalized, to the same standard of measurement to account for differences in the depth of sequencing for each sample. In a paper (Optimal Scaling of Digtial Transcriptomes) published today in PLOS ONE, researchers at ISB compare several methods currently used to normalize gene expression data and describe new algorithms developed at ISB that outperform commonly used normalization methods.

“The two most common normalization methods either trust a single gene to be ‘constant’ across all samples, or assume that all cells have the same total amount of transcribed RNA,” explained Dr. Gustavo Glusman, lead author of the paper. “Both assumptions are often wrong. Our methods can normalize digital transcriptomes without relying on either.” The new methods yield robustly normalized expression values, which is a prerequisite for the identification of differentially expressed and tissue-specific genes as potential biomarkers.

About Dr. Martin Shelton: Martin is a postdoc in the Hood lab at ISB. He is a member of ISB's Editorial Board.

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How ISB’s Systems Approach Finds New Biological Insight from Existing Big-Data Sets http://isbmolecularme.com/how-isbs-systems-approach-finds-new-biological-insight-from-existing-big-data-sets/ http://isbmolecularme.com/how-isbs-systems-approach-finds-new-biological-insight-from-existing-big-data-sets/#comments Fri, 01 Nov 2013 17:20:02 +0000 http://isbmolecularme.com/?p=1899 3 Bullets:
  • There exist copious amounts of public research data that can reveal new biological information if they are integrated and analyzed.
  • One of ISB's specialties is the ability to apply systems approaches to develop methods to integrate and analyze data.
  • In the latest publication, ISB demonstrates an open-access computational strategy that can help any researcher capitalize on large data sets.

By Dr. Nitin Baliga

Systems biology promises to open a new world in human healthcare by integrating high throughput (big data) experiments to quickly discover novel biology and thus develop more effective treatment options. However, systems biology studies are often challenged by the problem of scale. In other words, how does one get from an abstract model encompassing all genes to specific experiments that reveal novel insight into biological mechanisms underlying health and disease. A team led by John Aitchison and Nitin Baliga has developed a template to discover novel biology from large amount of data that are now available for numerous organisms of medical and environmental importance. The work was published today in the journal Nucleic Acids Research.

Sam Danziger, a bioinformatics scientist working jointly under Drs. Aitchison and Baliga at ISB, developed a computational strategy to reconstruct the network of gene interactions within yeast using publicly available data from about 1500 experiments that were performed by different researchers across the world. Danziger and co-workers used this model to investigate how yeast cells regulate peroxisome function. Peroxisomes are medically important organelles that have been implicated in metabolic disorders and also the human innate immune response. Although a great deal of peroxisome biology has been characterized, much of the early events and mechanisms responsible for induction of this organelle are poorly understood. By iteratively refining the model, Danziger and co-workers discovered new genes and interactions across the varied hierarchies of genetic information processing to regulate peroxisome function, providing new leads for further studies in more complex mammalian cells. 

Most notably, this study provides a template for molecular systems approaches to exploit large public data sets, which are increasingly available for varied biological systems. Applications include fundamental research into genetic regulation, identification of drug targets in diseased or pathogen-infected cells and engineering microorganisms for remediation or production of biomaterials.

About Dr. Nitin Baliga: Nitin is the Director and SVP of ISB. He is a founding faculty member of ISB and the faculty science advisor for the ISB Editorial Board.

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Systems Approach to Innovation Helps Extract More Data http://isbmolecularme.com/systems-approach-to-innovation-helps-extract-more-data/ http://isbmolecularme.com/systems-approach-to-innovation-helps-extract-more-data/#comments Thu, 31 Oct 2013 18:16:27 +0000 http://isbmolecularme.com/?p=1883 3 Bullets:
  • Technology lag affects the study of proteins, which when quantified can indicate disease or wellness.
  • ISB uses systems approach to innovate and transcend technology limitations.
  • ISB co-develops new technique and software suite to increase protein detection rate.

By Dr. Kristian Swearingen

Scientific breakthroughs are often contingent on available technology. In the case of measuring proteins, the mass spectrometers that exist today aren’t fast enough to detect all the proteins that might be present in a given sample. So it’s necessary for researchers to create ways to push the current technology in order to improve protein detection capabilities.

The latest advancement is the result of a collaboration between ISB and a team of scientists at Stockholm University and KTH in Sweden to develop a new software technique for extracting more protein identifications from experimental data. The technique, dubbed iAMT (in silico accurate mass and time), was published in September in the Journal of Proteome Research. ISB researcher Michael Hoopmann in the Moritz group conceived iAMT and co-developed the suite of software tools that drive the method. In addition to enhancing future efforts, iAMT can be used to re-analyze previous experiments to find proteins that were missed.

The study of proteins by the technique called  proteomics is important because the quantitative differences of certain proteins can indicate disease or wellness. Genes encode proteins, and there are many different interconnected biological processes taking place at any given time that can influence or be influenced by whether a gene expresses those proteins. The systems biology approach to proteomics is to study the proteome as a dynamic network of interacting components. It is therefore critical to systems biology to be able to detect as many proteins as possible.

In a typical proteomics experiment, proteins are cleaved into fragments called peptides, which are separated by liquid chromatography and analyzed in a mass spectrometer – a technique called “shotgun proteomics.” Within the mass spectrometer the peptides are isolated one at a time and fragmented. The resulting signal is compared against expected signals predicted from the gene database and used to identify the peptide. If enough quality peptide identifications are made, the protein identity can be inferred.

Currently, it is not possible to identify or quantitate every protein present in a complex sample, such as human cells. The human proteome is estimated to consist of more than 600,000 unique peptides with millions more when post-translational modifications are also considered. Detecting each of these peptides in a single experiment would require an instrument many times faster than existing mass spectrometers to individually fragment the hundreds of thousands of peptides present in a sample. Consequently, only a fraction of the peptides in a sample are selected for fragmentation, and of these, an even smaller fraction produce signal of sufficiently high quality to give a confident identification.

ISB researchers and their collaborators developed iAMT’s suite of software tools that can increase the number of protein identifications in complex samples by up to 7 percent by finding evidence for proteins that were not identified by MS/MS fragmentation. Even if a peptide of a particular protein is never fragmented, its mass may still be recorded by the mass spectrometer but this information is not used by current mass spectrometry peptide identification algorithms. This information, combined with the chromatographic retention time, can be used to narrow down the potential identity of the peptide to a handful of candidates. Sophisticated algorithms were developed as part of this collaboration between ISB and KTH that predict the behavior of peptides thought to be present and search the data for evidence of real, unidentified peptides that match the predictions. Rigorous statistical analysis of this indirect evidence increases the percentage of high-confidence protein identifications. Additionally, by detecting more peptides, the method increases the overall confidence level of protein identifications.

While researchers wait for proteomics technology to improve, new ways of analyzing data will enable researchers to push existing technology to its limits. The iAMT approach is an example of using systems level thinking to extract all the information possible from experimental data.

About Dr. Kristian Swearingen: Kristian is a research scientist in the Moritz group at ISB. He is also a member of ISB's editorial board.

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